Uncertainty quantification in natural frequency of composite plates - an artificial neural network based approach

Dey, Sudip, Mukhopadhyay, Tanmoy, Spickenheuer, Axel, Gohs, Uwe and Adhikari, S. (2016) Uncertainty quantification in natural frequency of composite plates - an artificial neural network based approach. Composites and Advanced Materials, 25 (2), 43-48. (doi:10.1177/096369351602500203).

Abstract

This paper presents the stochastic natural frequency for laminated composite plates by using artificial neural network (ANN) model. The ANN model is employed as a surrogate and is trained by using Latin hypercube sampling. Subsequently the stochastic first two natural frequencies are quantified with ANN based uncertainty quantification algorithm. The convergence of the proposed algorithm for stochastic natural frequency analysis of composite plates is verified and validated with original finite element method (FEM) in conjunction with Monte Carlo simulation. Both individual and combined variation of stochastic input parameters are considered to address the influence on the output of interest. The sample size and computational cost are reduced by employing the present approach compared to traditional Monte Carlo simulation.

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